| Speech dereverberation based on variance-normalized delayed linear prediction T Nakatani, T Yoshioka, K Kinoshita, M Miyoshi, BH Juang IEEE Transactions on Audio, Speech, and Language Processing 18 (7), 1717-1731, 2010 | 505 | 2010 |
| The reverb challenge: A common evaluation framework for dereverberation and recognition of reverberant speech K Kinoshita, M Delcroix, T Yoshioka, T Nakatani, A Sehr, W Kellermann, ... Applications of Signal Processing to Audio and Acoustics (WASPAA), 2013 IEEE …, 2013 | 473 | 2013 |
| A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research K Kinoshita, M Delcroix, S Gannot, EA P. Habets, R Haeb-Umbach, ... EURASIP Journal on Advances in Signal Processing 2016, 1-19, 2016 | 423 | 2016 |
| Making machines understand us in reverberant rooms: Robustness against reverberation for automatic speech recognition T Yoshioka, A Sehr, M Delcroix, K Kinoshita, R Maas, T Nakatani, ... IEEE Signal Processing Magazine 29 (6), 114-126, 2012 | 338 | 2012 |
| Generalization of multi-channel linear prediction methods for blind MIMO impulse response shortening T Yoshioka, T Nakatani IEEE Transactions on Audio, Speech, and Language Processing 20 (10), 2707-2720, 2012 | 318 | 2012 |
| Improving transformer-based end-to-end speech recognition with connectionist temporal classification and language model integration T Nakatani proc. INTERSPEECH 2019, 1408-1412, 2019 | 271 | 2019 |
| The NTT CHiME-3 system: Advances in speech enhancement and recognition for mobile multi-microphone devices T Yoshioka, N Ito, M Delcroix, A Ogawa, K Kinoshita, M Fujimoto, C Yu, ... 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU …, 2015 | 269 | 2015 |
| Robust MVDR beamforming using time-frequency masks for online/offline ASR in noise T Higuchi, N Ito, T Yoshioka, T Nakatani 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 267 | 2016 |
| Suppression of late reverberation effect on speech signal using long-term multiple-step linear prediction K Kinoshita, M Delcroix, T Nakatani, M Miyoshi IEEE transactions on audio, speech, and language processing 17 (4), 534-545, 2009 | 253 | 2009 |
| Speakerbeam: Speaker aware neural network for target speaker extraction in speech mixtures K ®molíková, M Delcroix, K Kinoshita, T Ochiai, T Nakatani, L Burget, ... IEEE Journal of Selected Topics in Signal Processing 13 (4), 800-814, 2019 | 227 | 2019 |
| Single channel target speaker extraction and recognition with speaker beam M Delcroix, K Zmolikova, K Kinoshita, A Ogawa, T Nakatani 2018 IEEE international conference on acoustics, speech and signal …, 2018 | 214 | 2018 |
| Blind separation and dereverberation of speech mixtures by joint optimization T Yoshioka, T Nakatani, M Miyoshi, HG Okuno IEEE Transactions on Audio, Speech, and Language Processing 19 (1), 69-84, 2010 | 196 | 2010 |
| Blind speech dereverberation with multi-channel linear prediction based on short time Fourier transform representation T Nakatani, T Yoshioka, K Kinoshita, M Miyoshi, BH Juang 2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008 | 194 | 2008 |
| Speech processing for digital home assistants: Combining signal processing with deep-learning techniques R Haeb-Umbach, S Watanabe, T Nakatani, M Bacchiani, B Hoffmeister, ... IEEE Signal processing magazine 36 (6), 111-124, 2019 | 192 | 2019 |
| Exploring multi-channel features for denoising-autoencoder-based speech enhancement S Araki, T Hayashi, M Delcroix, M Fujimoto, K Takeda, T Nakatani 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 134 | 2015 |
| Online MVDR beamformer based on complex Gaussian mixture model with spatial prior for noise robust ASR T Higuchi, N Ito, S Araki, T Yoshioka, M Delcroix, T Nakatani IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (4), 780-793, 2017 | 128 | 2017 |
| LINEAR PREDICTION-BASED DEREVERBERATION WITH ADVANCED SPEECH ENHANCEMENT AND RECOGNITION TECHNOLOGIES FOR THE REVERB CHALLENGE M Delcroix, T Yoshioka, A Ogawa, Y Kubo, M Fujimoto, N Ito, K Kinoshita, ... | 128 | 2014 |
| Speaker-aware neural network based beamformer for speaker extraction in speech mixtures K ®molíková, M Delcroix, K Kinoshita, T Higuchi, A Ogawa, T Nakatani Proc. Interspeech 2017, 2655-2659, 2017 | 127 | 2017 |
| A multichannel MMSE-based framework for speech source separation and noise reduction M Souden, S Araki, K Kinoshita, T Nakatani, H Sawada IEEE Transactions on Audio, Speech, and Language Processing 21 (9), 1913-1928, 2013 | 127 | 2013 |
| Improving speaker discrimination of target speech extraction with time-domain speakerbeam M Delcroix, T Ochiai, K Zmolikova, K Kinoshita, N Tawara, T Nakatani, ... ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 122 | 2020 |
Keisuke KinoshitaResearch Scientist at GoogleE-mail megerősítve itt: ieee.org
